This site is about everything digital, giving an update on new things as I learn

Category: Technology

Lawrence Burns is a veteran of the automative industry. Having worked his entire professional career in the car industry – in Detroit, the birthplace of modern car manufacturing no less – you might expect Burns to be apprehensive about ‘change’ and modern technology. The opposite couldn’t be more true of Burns, since he’s been an advocate for driverless cars for the past 15+ years, starting his foray into this field whilst at General Motors.

The book starts off with the story of the “DARPA Challenge” in 2004 and how this helped shaped learning and development with respect to driverless cars. Burns gives the reader a good close-up of the experiences and learnings from one of the teams that took part in this challenge. At this first DARPA challenge, every vehicle that took part crashed, failed or caught fire, highlighting the early stage of driverless technology at the time.

Bob Lutz, former executive of Ford, Chrysler and General Motors, wrote an essay last year titled “Kiss the good times goodbye”, in which he makes a clear statement about the future of the automotive industry: “The era of the human-driven automobile, its repair facilities, its dealerships, the media surrounding it – all will be gone in 20 years.” There’s no discussion that driverless cars are coming, especially that both car and technology giants are busy developing and testing. When I attended a presentation by Burns a few months agogo, he showed the audience examples of both self driving cars and trucks:

In “Autonomy”, Burns brings Lutz’ predictions to life through the fictitious example of little Tommy and his family. In this example, Tommy steps into a driverless which has been programmed to take him to school in the morning. Tommy’s grandma will be picked up by a driverless two-person mobility pod to take her to a bridge tournament. Burns describes a world where car ownership will be a thing of the past; people using publicly available fleets of self driving cars instead.

Together with Chris Borroni-Bird, Burns has done extensive research into the potential impact of an electronic self driven car, looking at metrics such as “total expense per mile”, “cost savings per mile” and “estimated number of parts”. Borroni-Bird and Burns provide some compelling stats, especially when contrasted against conventional cars. Reading these stats helps to make the impact of driverless technology a lot more tangible, turning it from science fiction or future music into a realistic prospect.

Main learning point: “Autonomy” by Lawrence is an insightful book about a driverless future, written by a true connoisseur of the car industry and the evolution of driverless technology.

Dr. Kai-Fu Lee is the chairman and CEO of Sinovation Ventures, a China based tech focused investment firm. Previous to becoming a full-time investor, Lee held positions at Google, Microsoft and Apple. A large part of that career, Lee spent working on data and Artificial Intelligence (‘AI’), both in the US and in China. In “AI Superpowers – China, Silicon Valley and the New World Order” Lee bundles his experiences and insights to describe the progress that China and the US have made and are making in the field of AI.

AI Superpowers contains a heap of valuable insights as well as predictions about the impact of technology power that both the US and China have been racking up. These are the main things that I took away from reading AI Superpowers:

US and China, contrasting cultures – Lee starts the book by writing about the contrasts in business culture between the US and China: “China’s startup culture is the yin to Silicon Valley’s yang: instead of being mission-driven, Chinese companies are first and foremost market-driven.” Lee goes on to explain that the ultimate goal of Chinese companies is “to make money, and they’re willing to create any product, adopt any model, or go into any business that will accomplish that objective.” This mentality help to explain the ‘copycat’ attitude that Chinese companies have had historically. Meituan, for example, is a group-discount website which sells vouchers from merchants for deals which started as the perfect counterpart of US-based Groupon.

“Online-to-Offline” (‘O2O”) – O2O describes the conversion of online actions into offline services. Ride-sharing services like Uber and Lyft are great examples of the new O2O model. In China, Didi copied this model and tailored it to local conditions. Didi was followed by other O2O plays such as Dianping, a food delivery service which subsequently merged with the aforementioned Meituan company, and Tujia, a Chinese version of Airbnb. Lee also mentions WeChat and Alipay, describing how both companies completely overturned China’s all-cash economy. More recently, bike-sharing startups Mobike (see Fig. 1 below) and ofo which supplied tens of millions of internet-connected bicycles, distributing them across them about major Chinese cities and now across the globe.

China catching up quickly in the AI department – Having read the story of image recognition algorithm ResNet, and how its inventors moved from Microsoft to join AI startups in China, I can see how China as a country is quickly catching up with the technology stalwart that is Silicon Valley. One of these image recognition startups, Face +++, has quickly become a market leader in face / image recognition technology, leapfrogging the likes of Google, Microsoft and Facebook along the way.

The four waves of AI – In AI Superpowers, Lee argues that what he calls the “AI revolution” will not happen overnight. Instead, AI will wash over us in four waves: internet AI, business AI, perception AI, and autonomous AI (see Fig. 2 below). This part of the book really struck a chord with me, as it brings to life how AI is likely to evolve over the coming years, both in terms of practical applications and use cases.

Main learning point: I’d highly recommend “AI Superpowers” to anyone interested in learning more about how China and the US are furthering the development of AI and the impact of this development on our daily lives.

First wave: Internet AI – Internet AI is largely about using AI algorithms as recommendation engines: systems that learn our personal preferences and then serve up content hand-picked for us. Toutiao, sometimes called “the Buzzfeed of China”, is a great example of this first wave of AI; its “editors” are algorithms.

Second wave: Business AI – First wave AI leverages the fact that internet users are automatically labelling data as they browse. Business AI, the second wave of AI, takes advantage of the fact that traditional companies have also been automatically labelling huge quantities of data for decades. For instance, insurance companies have been covering accidents and catching fraud, banks have been issuing loans and documenting repayment rates, and hospitals have been keeping records of diagnoses and survival rates. Business AI mines these data points and databases for hidden correlations that often escape the naked eye and the human brain. RXThinking, an AI based diagnosis app, is a good example in this respect.

Third wave: Perception AI – Third wave AI is all about extending and expanding this power throughout our lived environment, digitising the world around us through the proliferation of sensors and smart devices. These devices are turning our physical world into digital data that can then be analysed and optimised by deep-learning algorithms. For example, Alibaba’s City Brain is digitising urban traffic flows through cameras and object-recognition.

My quick summary of Forest before using the app – I think I first heard Nir Eyal, who specialised in consumer psychology, talk about Forest. Given that Nir mentioned the app, I can imagine Forest impacts people behaviour, helping them achieve specific outcomes.

How does Forest explain itself in the first minute? – “Stay focused, be presented” is Forest’s strap line which I see first. This strap line is followed swiftly followed by a screen that says “Plant a Tree” and explains that “Whenever you want to focus on your work, plant trees.” This suggest to me that Forest is an app which aims to help people focus on their work and eradicate all kinds of distractions.

How does Forest work? – The app first explains its purpose in a number of nicely designed explanatory screens.

After clicking “Go”, I land on a screen where I can adjust time; presumably the time during which I want to focus and avoid any interruptions.

I set the time at 10 minutes and click “Plant”. I love how, as the time progresses, the messages at the top of the screen keep alternating, from “Don’t look at me!” to “Don’t look at me!” to “Hang in there!” Nice messages to help keep me focus and not fall prey to checking my phone. At any stage, I can opt to “Give up” which presumably means that the tree that I’ve been planting – through staying focused – will be killed.

I’m motivated to see this through and plant my first tree. When I complete my 10 minutes of uninterrupted time, I expect to see a nice tree right at the end of it. Try and imagine my disappointment when I don’t see a tree but instead am encouraged to create a Forest acount

Did Forest deliver on my expectations? – I can see how Forest helps people to focus and avoid checking their phone constantly. Just want to explore the gamification element of the app a bit more.

Can the whole process of getting a mortgage made a lot easier!? Whether you’re looking to buy a home or refinance your current one, the mortgage process can be a real pain in the neck: slow, stressful and opaque. Given the emergence of players such as Trussle, Habito – both UK-based online mortgage brokers – and my professional interest from leading product at Settled, I’m keen to explore this further.

My quick summary of Rocket Mortgage before using it: I expect a product that makes it very quick and easy for a me as a consumer to apply for a mortgage.

How does Rocket Mortgage explain itself in the first minute: “You May Be Surprised to See How Much You Can Save – Can’t Hurt to Look” and “We’ve Reinvented the Mortgage Process to Put the Power in Your Hands” are two strap-lines on Rocket Mortgage homepage that stand out to me. Both lines are ‘above the fold’ and do make me curious to learn more about what Rocket Mortgage does (differently) to established mortgage providers.

How does Rocket Mortgage work? Mortgage applicants can submit their personal and financial information online (“Share Your Info”), and they receive a mortgage quote in return. This initial quote can be reviewed and customised to meet one’s personal needs and circumstances (“Explore Your Options”).

Let’s look at the individual steps in more detail:

User answer pre-approval questions

To apply for a Rocket Mortgage loan, you’ll first need to create an account by entering your name and email address, followed by choosing a password. Once you’ve clicked the “Save & Continue” button, you’ll be presented with a number of questions about your personal situation, both from a personal and a financial point of view:

User uploads personal assets

Rocket Mortgage will connect to your bank account(s) and your asset information will then be uploaded automatically onto the platform. You can then update the information or remove assets from consideration from your mortgage application, , after the boxes have been auto-filled. With the advent of PSD2 and open banking, I expect loads of US mortgage lenders and startups to enable a similar synchronisation with a user’s personal accounts.

If you have any other financial assists, like investments in shares via platforms such as Betterment and Wealthify, you will need to enter this data manually as well as related documents. The same applies to Rocket Mortgage requiring you to enter specific info to be able to generate a personal credit report and score. In future, I expect platforms like these to seamlessly integrated with credit score companies like Experian and Equifax.

User explores options

User obtains a mortgage rate

Once you’ve locked down a mortgage rate, there’s a separate Rocket Mortgage online tool which lets you finalise the mortgage.

Who else is doing this? I had a brief look at “mello”, the digital loan platform by loanDepot, and the product and its experience feels quite similar to Rocket Mortgage. In the UK, Molo is a new player on the scene, promising to “reimagine mortgages.”

Main learning point: It’s clear for everyone to see that these players are aiming to make the experience of applying for a mortgage as intuitive, transparent and quick as possible.

Just a short post this time, as I just wanted to share my excitement about the likes of Square and Klarna becoming banks (eventually). As an outsider looking in, I can see the rationale for companies like Square and Klarna, payments platforms, for becoming full blowing banking entities:

Logical extension of the payments ecosystem – Given that Square and Klarna already process payment transactions for thousands of merchants and their customers, it means that they’ve got a strong foot in the door with small businesses. It therefore makes total sense to offer new products and services to both merchants and their customers.

Data, data, data – I can imagine that with the amount of transactional data being processed, Square and Klarna no doubt have built up great customer and merchant data profiles, and are now looking to further monetise on this customer understanding. Offering lending products jumps out at me as a key reason for Square and Klarna wanting to become banks. This pattern fits well on the trend involving challenger banks like Monzo and Chime starting out with limited features, but gradually expanding into fully fledged bank accounts.

Hook at point of sale – Being able to engage with both consumers and merchants at the point of sale feels like a pretty strong hook to me! Loved how backend payment platform Adyen recently got valued at $8.3 billion, and it shows you that the financial sector is way off from calming down.

Main learning point: Whilst there are concerns about small businesses being impacted negatively by the likes of Square becoming banks, I’m excited by the ongoing disruption of the financial sector. Recent applications for banking licenses by Square and Klarna are a sign that the Fintech startups and challengers are scaling. As long scaling doesn’t happen at the detriment of the customer – both consumers and merchants – this can only be a good thing!

These smart glasses connect to a feed which taps into China’s state database to detect out potential criminals using facial recognition. Officers can identify suspects in a crowd by snapping their photo and matching it to their internal database.

Wrong360 is a Chinese peer-to-peer lending app which aims to make obtaining a loan as simple as possible. When users of the Wrong360 app enter the amount of loan, period, and purpose, the platform will automatically do the match and output a list of banks or credit agencies corresponding to the users’ requests. On the list, users can find the institution names, products, interests rate, gross interests, monthly payment, and the available periods, etc. Applying for a loan can done fully online, and the app uses facial recognition as part of the loan application process.

Product 3 — Security camera

Security cameras in public places to help police officers and shopkeepers by improved ways of face matching. Traditionally, face matching is based on trait description of someone’s facial features and the special distance between these features. Now, by extracting the geometric descriptions of the parts of the eyes, nose, mouth, chin, etc. and the structural relationship between them, search matching is performed with the feature templates stored in the database. When the similarity exceeds the set threshold, the matching results are shared.

Whether it’s “SenseTotem” — which is being used for surveillance purposes — or “SensePhoto” — which uses facial recognition technology for messaging apps and mobile cameras — it all comes from the same company: SenseTime.

The company has made a lot of progress in a relatively short space of time with respect to artificial intelligence based (facial) recognition. The Chinese government has been investing heavily in creating an ecosystem for AI startups, with Megvii as another well known exponent of China’s AI drive.

A project with the code name “Viper” is the latest in the range of products that SenseTime is involved. I’m intrigued and slightly scared by this project which is said to focus on processing thousands of live camera feeds (from CCTV, to traffic cameras to ATM cameras), processing and tagging people and objects. SenseTime is rumoured to want to sell the Viper surveillance service internationally, but I can imagine that local regulations and data protection rules might prevent this kind of ‘big brother is watching you’ approach to be rolled out anytime soon.

Main learning point: It seems that SenseTime is very advanced with respect to facial recognition, using artificial intelligence to combine thousands of (live) data sources. You could argue that SenseTime isn’t the only company building this kind of technology, but their rapid growth and technological as well as financial firepower makes them a force to be reckoned with. That, in my mind, makes SenseTime very special indeed.

The main driver for this app review of Blinkist is simple: I heard a fellow product manager talking about it and was intrigued (mostly by the name, I must add).

My quick summary of Blinkist (before using it) – “Big ideas in small packages” is what I read when I Google for Blinkist. I expect an app which provides me with executive type summaries of book and talks, effectively reducing them to bitesize ideas and talking points.

How does Blinkist explain itself in the first minute? – When I go into Apple’s app store and search for Blinkist, I see a strapline which reads “Big ideas from 2,000+ nonfiction books” and “Listen or read in just 15 minutes”. There’s also a mention of “Always learning” which sounds good …

Getting started, what’s the process like? (1) – I like how Blinkist lets me swipe across a few screens before deciding whether to click on the “Get started” button. The screens use Cal Newport’s “Deep Work” book as an explain to demonstrate the summary Blinkist offers of the book, the 15 minute extract to read or listen to, and how one can highlight relevant bits of the extract. These sample screens give me a much better idea of what Blinkist is about, before I decide whether to sign up or not.

Getting started, what’s the process like? (2) – I use Facebook account to sign up. After I clicked on “Connect with Facebook” and providing authorisation, I land on this screen which mentions “£59.99 / year*”, followed by a whole lot of small print. Hold on a minute! I’m not sure I want to commit for a whole year, I haven’t used Blinkist’s service yet! Instead, I decide to go for the “Subscribe & try 7 days for free” option at the bottom of the screen.

Despite my not wanting to pay for the Blinkist service at this stage, I’m nevertheless being presented with an App Store screen which asks me to confirm payment. No way! I simply get rid of this screen and land on a – much friendlier – “Discover” screen.

To start building up my own library I need to go into the “Discover” section and pick a title. However, when I select “Getting Things Done” which is suggested to me in the Discover section, I need to unlock this first by start a free 7-day trial. I don’t want to this at this stage! I just want to get a feel for the content and for what Blinkist has to offer, and how I can best get value out of its service. I decide to not sign up at this stage and leave things here … Instead of letting me build up my library, invest in Blinkist and its content and I only then making me ‘commit’, Blinkist has gone for a free trial and subscription model instead. This is absolutely fine, but doesn’t work for me unfortunately, as I just want to learn more before leaving my email address, committing to payment, etc.